Recognizing depression in patients with Parkinson's disease: accuracy and specificity of two depression rating scale

Arq Neuropsiquiatr. 2006 Jun;64(2B):407-11. doi: 10.1590/s0004-282x2006000300011.

Abstract

This study aimed to find cut-off scores for the Montgomery-Asberg rating scale (MADRS) and the Beck depression inventory (BDI) that can relate to specific clinical diagnoses of depression in Parkinson s disease (PD). Mild and moderate PD patients (n=46) were evaluated for depression according to the DSM IV criteria. All patients were assessed with the MADRS and the BDI. A "receiver operating characteristics" (ROC) curve was obtained and the sensibility, specificity, positive and the negative predictive values were calculated for different cut-off scores of the MADRS and the BDI. The Kappa statistic was calculated for different cut-off scores to assess the agreement between the clinical judgment and both scales. Depression was present in 18 patients. MADRS cut-off scores of 6 and 10 showed Kappa 0.5 and 0.56, respectively. Specificity of cut-off score of 6 was 78.6% and of cut-off score of 10 was 96.4%. Kappa agreement of BDI cut-off scores of 10 and 18 were 0.36 and 0.62, respectively. Specificity was 60.7% for 10 and 92.9% for 18. Both rating scales show similar accuracy within the ROC curves (84.3% for MADRS and 79.7% for BDI). The MADRS and the BDI show a good accuracy and correlation to the clinical diagnosis when a cut-off score of 10 is used to MADRS and a cut-off score of 18 is used to BDI to recognize depression in mild to moderate PD patients. This may help clinicians to recognize depression in PD.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Depression / diagnosis*
  • Depression / etiology
  • Female
  • Humans
  • Male
  • Middle Aged
  • Parkinson Disease / psychology*
  • Predictive Value of Tests
  • Psychiatric Status Rating Scales*
  • Psychometrics
  • ROC Curve
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Severity of Illness Index